2017-02-26 68 views
0

我正在使用Spark 2.1.0並嘗試連接Cassandra集羣。我使用了最新的閃電。我已經設置了默認的配置如下 默認:無法使用Spark會話加載Cassandra表,Sparklyr和R

# local-only configuration 
    sparklyr.cores.local: !expr parallel::detectCores() 
    spark.sql.shuffle.partitions.local: !expr parallel::detectCores() 

    # cassandra settings 
spark.cassandra.connection.host:<Cassandra IP> 
spark.cassandra.auth.username: <uid> 
spark.cassandra.auth.password:<pass> 

sparklyr.defaultPackages: 
- com.databricks:spark-csv_2.11:1.5.0 
- com.datastax.spark:spark-cassandra-connector_2.11:2.0.0-RC1 
- com.datastax.cassandra:cassandra-driver-core:3.1.4 

將瓶子位於根目錄所在的源文件的位置。

我已經執行了以下操作。一切都很好,直到我試圖調用read函數。我已經明確設置了jar的位置。

> library(sparklyr) 
    > config <- spark_config() 
    Warning message: 
    In readLines(input, encoding = "UTF-8") : 
     incomplete final line found on '/home/bsc/BSCAnalytics/config.yml' 
    > config[["sparklyr.jars.default"]] <- c("/home/bsc/BSCAnalytics/cassandra-driver-core-3.1.4.jar") 
    > 
    > sc <- spark_connect(master = "local", version = "2.1.0") 
    Warning message: 
    In readLines(input, encoding = "UTF-8") : 
     incomplete final line found on '/home/bsc/BSCAnalytics/config.yml' 
    > Spark.session <- sparklyr::invoke_static(sc, "org.apache.spark.sql.SparkSession", "builder") %>% sparklyr::invoke("config", "spark.cassandra.connection.host", "<Cassandra IP>") %>% sparklyr::invoke("getOrCreate") 

當我嘗試調用read函數時,運行時無法找到罐子。我親眼目睹了以下錯誤:

> event_df <- invoke(Spark.session, "read") %>% invoke("format", "org.apache.spark.sql.cassandra") %>% invoke("option", "keyspace", "kps") %>% invoke("option", "table", "tab_event") %>% invoke("load") 
Error: java.lang.ClassNotFoundException: Failed to find data source: org.apache.spark.sql.cassandra. Please find packages at http://spark.apache.org/third-party-projects.html 
    at org.apache.spark.sql.execution.datasources.DataSource$.lookupDataSource(DataSource.scala:569) 
    at org.apache.spark.sql.execution.datasources.DataSource.providingClass$lzycompute(DataSource.scala:86) 
    at org.apache.spark.sql.execution.datasources.DataSource.providingClass(DataSource.scala:86) 
    at org.apache.spark.sql.execution.datasources.DataSource.resolveRelation(DataSource.scala:325) 
    at org.apache.spark.sql.DataFrameReader.load(DataFrameReader.scala:152) 
    at org.apache.spark.sql.DataFrameReader.load(DataFrameReader.scala:125) 
    at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method) 
    at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:62) 
    at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43) 
    at java.lang.reflect.Method.invoke(Method.java:498) 
    at sparklyr.Invoke$.invoke(invoke.scala:94) 
    at sparklyr.StreamHandler$.handleMethodCall(stream.scala:89) 
    at sparklyr.StreamHandler$.read(stream.scala:55) 
    at sparklyr.BackendHandler.channelRead0(handler.scala:49) 
    at sparklyr.BackendHandler.channelRead0(handler.scala:14) 
    at io.netty.channel.SimpleChannelInboundHandler.channelRead(SimpleChannelInboundHandler.java:105) 
    at io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:367) 
    at io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:353) 
    at io.netty.channel.AbstractChannelHandlerContext.fireChannelRead(AbstractChannelHandlerContext.java:346) 
    at io.netty.handler.codec.MessageToMessageDecoder.channelRead(MessageToMessageDecoder.java:102) 
    at io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:367) 
    at io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:353) 
    at io.netty.channel.AbstractChannelHandlerContext.fireChannelRead(AbstractChannelHandlerContext.java:346) 
    at io.netty.handler.codec.ByteToMessageDecoder.fireChannelRead(ByteToMessageDecoder.java:293) 
    at io.netty.handler.codec.ByteToMessageDecoder.channelRead(ByteToMessageDecoder.java:267) 
    at io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:367) 
    at io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:353) 
    at io.netty.channel.AbstractChannelHandlerContext.fireChannelRead(AbstractChannelHandlerContext.java:346) 
    at io.netty.channel.DefaultChannelPipeline$HeadContext.channelRead(DefaultChannelPipeline.java:1294) 
    at io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:367) 
    at io.netty.channel.AbstractChannelHandlerContext.invokeChannelRead(AbstractChannelHandlerContext.java:353) 
    at io.netty.channel.DefaultChannelPipeline.fireChannelRead(DefaultChannelPipeline.java:911) 
    at io.netty.channel.nio.AbstractNioByteChannel$NioByteUnsafe.read(AbstractNioByteChannel.java:131) 
    at io.netty.channel.nio.NioEventLoop.processSelectedKey(NioEventLoop.java:652) 
    at io.netty.channel.nio.NioEventLoop.processSelectedKeysOptimized(NioEventLoop.java:575) 
    at io.netty.channel.nio.NioEventLoop.processSelectedKeys(NioEventLoop.java:489) 
    at io.netty.channel.nio.NioEventLoop.run(NioEventLoop.java:451) 
    at io.netty.util.concurrent.SingleThreadEventExecutor$2.run(SingleThreadEventExecutor.java:140) 
    at io.netty.util.concurrent.DefaultThreadFactory$DefaultRunnableDecorator.run(DefaultThreadFactory.java:144) 
    at java.lang.Thread.run(Thread.java:745) 
Caused by: java.lang.ClassNotFoundException: org.apache.spark.sql.cassandra.DefaultSource 
    at java.net.URLClassLoader.findClass(URLClassLoader.java:381) 
    at java.lang.ClassLoader.loadClass(ClassLoader.java:424) 
    at java.lang.ClassLoader.loadClass(ClassLoader.java:357) 
    at org.apache.spark.sql.execution.datasources.DataSource$$anonfun$25$$anonfun$apply$13.apply(DataSource.scala:554) 
    at org.apache.spark.sql.execution.datasources.DataSource$$anonfun$25$$anonfun$apply$13.apply(DataSource.scala:554) 
    at scala.util.Try$.apply(Try.scala:192) 
    at org.apache.spark.sql.execution.datasources.DataSource$$anonfun$25.apply(DataSource.scala:554) 
    at org.apache.spark.sql.execution.datasources.DataSource$$anonfun$25.apply(DataSource.scala:554) 
    at scala.util.Try.orElse(Try.scala:84) 
    at org.apache.spark.sql.execution.datasources.DataSource$.lookupDataSource(DataSource.scala:554) 
    ... 39 more 

回答

0

您可以使用這樣的事情:

library(sparklyr) 

config <- spark_config() 
config[["sparklyr.defaultPackages"]] <- c(
    "datastax:spark-cassandra-connector:2.0.0-RC1-s_2.11") 

sc <- spark_connect(master = "local", version = "1.6.1", config = config) 

df <- sparklyr:::spark_data_read_generic(
    sc, 
    "org.apache.spark.sql.cassandra", 
    "format", list(
    keyspace = "dev", 
    table = "emp" 
)) %>% invoke("load") 

cassandra_tbl <- sparklyr:::spark_partition_register_df(
    sc, 
    df, 
    name = "emp", 
    repartition = 0, 
    memory = FALSE) 

cassandra_tbl 

又見https://github.com/rstudio/sparklyr/issues/520

+0

哈維爾嗨, 感謝。我想和大家分享如下,請過目細節,並尋求您的建議: 我們的火花(2.1)集羣不在同一位置與卡桑德拉(3.X)節點 卡桑德拉固定用的用戶ID和密碼 請讓我知道以下內容: 我應該在哪裏放置Spark Cassandra連接器jar,Sparlyr將如何引用它?看起來你正在將maven屬性傳遞給設置配置參數 的功能。我們在哪裏傳遞羣集IP,用戶ID和密碼? 我們如何在DF中加載凍結或其他Cassandra複雜對象以進一步分析? – SCB

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